Fractional response analysis reveals logarithmic cytokine responses in cellular populations

• Published in: Nature communications Vol. 12; no. 1; p. 4175
• Main Authors: Nienałtowski, Karol, Rigby, Rachel E, Walczak, Jarosław, Zakrzewska, Karolina E, Głów, Edyta, Rehwinkel, Jan, Komorowski, Michał
• Format: Journal Article
• Language: English
• Published: England Nature Publishing Group 07.07.2021; Nature Publishing Group UK; Nature Portfolio
• Subjects: 3T3 Cells; Animals; Cytokines; Healthy Volunteers; Heterogeneity; High-Throughput Screening Assays - methods; Humans; Interferon; Interferon Type I - immunology; Interferon Type I - metabolism; Leukocytes (mononuclear); Leukocytes, Mononuclear - immunology; Leukocytes, Mononuclear - metabolism; Mice; Models, Immunological; Models, Statistical; Multivariate analysis; Peripheral blood mononuclear cells; Populations; Primary Cell Culture; Signal Transduction - immunology; Signaling; Single-Cell Analysis; Software
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-021-24449-2

Although we can now measure single-cell signaling responses with multivariate, high-throughput techniques our ability to interpret such measurements is still limited. Even interpretation of dose-response based on single-cell data is not straightforward: signaling responses can differ significantly between cells, encompass multiple signaling effectors, and have dynamic character. Here, we use probabilistic modeling and information-theory to introduce fractional response analysis (FRA), which quantifies changes in fractions of cells with given response levels. FRA can be universally performed for heterogeneous, multivariate, and dynamic measurements and, as we demonstrate, quantifies otherwise hidden patterns in single-cell data. In particular, we show that fractional responses to type I interferon in human peripheral blood mononuclear cells are very similar across different cell types, despite significant differences in mean or median responses and degrees of cell-to-cell heterogeneity. Further, we demonstrate that fractional responses to cytokines scale linearly with the log of the cytokine dose, which uncovers that heterogeneous cellular populations are sensitive to fold-changes in the dose, as opposed to additive changes.